Vascular Cognitive Impairment and Dementia (VCID) is a leading cause of cognitive decline in Alzheimer?s disease and Related Dementias (ADRD). Compromised intracranial circulation and subsequent injury to brain parenchyma is the underlying cause of VCID related lesions. Vascular injury causative of VCID can range from large artery lesions to capillary perfusion defects. Therefore it is critical to understand the intracranial vascular health (IVH) status in the context of its different components ranging from large artery features to brain perfusion levels. However there are no existing methods to comprehensively assess IVH as a function of vascular features from large artery to capillary perfusion level. We will address this critical need by developing 3D vascular mapping of IVH that combines quantitative measurements of intracranial vessel wall, large to distal artery geometry, blood flow and tissue perfusion. Using the 3D vascular maps, we will test the hypothesis that 3D distribution of intracranial vascular features (vessel geometry, large artery blood flow and brain perfusion) is predictive of the individual?s cognitive status. To achieve this we will develop a 3D vascular score of IVH from the vascular map that is predictive of the propensity to brain parenchymal injury. Accordingly we will recruit 120 subjects with brain parenchymal injury (white matter hyperintensity (WMH), cortical/subcortical infarcts (CSI), and microhemorrhages (MH)) and perform structural brain and vascular MRI to construct a 3D vascular map predictive of parenchymal injury. Since the subjects in the parent study (NS092207) are recruited with known intracranial atherosclerosis or stroke and undergo vessel wall MRI scans, they are an ideal cohort for large artery lesions and CSI (60 subjects will be recruited into the supplement). We will recruit an additional 60 subjects with known WMH, CSI or MH based on hospital records. In addition to the fast high-resolution T1w vessel wall MRI from the parent study and arterial spin labeling (ASL), the vascular MRI will include an Improved Simultaneous Noncontrast Angiography and intraPlaque hemorrhage (iSNAP) sequence to map slow and fast flow vessels. Using a novel vessel priority 3D registration and intraCranial Artery Feature Extraction tool (iCAFE) we will develop 3D vascular maps. We will then develop a 3D vascular score that predicts parenchymal injury by combining information from vessel wall measures, iCafe, iSNAP and ASL. We will then test the hypothesis that baseline cognitive status by Montreal Cognitive Assessment (MOCA) score is predicted by the 3D vascular score in 120 subjects of the parent study. The technologies developed in this administrative supplement will allow study of the interaction between vascular status and post-stroke dementia in the parent cohort. It will also provide valuable information about the role of IVH in determining parenchymal injury and thereby enable future large scale studies to reduce vascular dementia.

Public Health Relevance

Parent Abstract (NS092207) Intracranial atherosclerotic disease (ICAD) represents 9-15% of strokes in the US and detection currently relies on stenosis measurement and likely underestimates the burden of this disease. In this proposal, we plan to 1) develop a multi-contrast 3D high resolution (HR) IVW MRI technique that consists of time efficient imaging sequences with a novel method for outer wall boundary detection; 2) develop image processing tools to characterize lesion size, distribution, main composition features and luminal surface condition-collectively named 3D wall imaging (3D-WALLI); 3) establish a scoring system with a stronger association with clinical symptoms and ischemic brain lesions than stenosis; and 4) study the score's power to predict secondary stroke and new ischemic lesions. The successful achievement of these aims will substantially expand our understanding of the relationship between ICAD vessel wall characteristics and risk of stroke, and 3D-WALLI will help define subgroups at higher risk which may represent a target population for future trials of novel interventions.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Koenig, James I
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University of Washington
Schools of Medicine
United States
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Watase, Hiroko; Sun, Jie; Hippe, Daniel S et al. (2018) Carotid Artery Remodeling Is Segment Specific: An In Vivo Study by Vessel Wall Magnetic Resonance Imaging. Arterioscler Thromb Vasc Biol 38:927-934
Rutman, Aaron M; Vranic, Justin E; Mossa-Basha, Mahmud (2018) Imaging and Management of Blunt Cerebrovascular Injury. Radiographics 38:542-563
Chen, Li; Mossa-Basha, Mahmud; Balu, Niranjan et al. (2018) Development of a quantitative intracranial vascular features extraction tool on 3D MRA using semiautomated open-curve active contour vessel tracing. Magn Reson Med 79:3229-3238
Mossa-Basha, Mahmud; Huynh, Thien J; Hippe, Daniel S et al. (2018) Vessel wall MRI characteristics of endovascularly treated aneurysms: association with angiographic vasospasm. J Neurosurg :1-9
Chen, Shuo; Ning, Jia; Zhao, Xihai et al. (2017) Fast simultaneous noncontrast angiography and intraplaque hemorrhage (fSNAP) sequence for carotid artery imaging. Magn Reson Med 77:753-758
Mossa-Basha, Mahmud; Shibata, Dean K; Hallam, Danial K et al. (2017) Added Value of Vessel Wall Magnetic Resonance Imaging for Differentiation of Nonocclusive Intracranial Vasculopathies. Stroke 48:3026-3033
Mossa-Basha, Mahmud; de Havenon, Adam; Becker, Kyra J et al. (2016) Added Value of Vessel Wall Magnetic Resonance Imaging in the Differentiation of Moyamoya Vasculopathies in a Non-Asian Cohort. Stroke 47:1782-8
Alexander, Matthew D; Yuan, Chun; Rutman, Aaron et al. (2016) High-resolution intracranial vessel wall imaging: imaging beyond the lumen. J Neurol Neurosurg Psychiatry 87:589-97
Zhou, Zechen; Wang, Jinnan; Balu, Niranjan et al. (2016) STEP: Self-supporting tailored k-space estimation for parallel imaging reconstruction. Magn Reson Med 75:750-61
Mossa-Basha, Mahmud; Alexander, Matthew; Gaddikeri, Santhosh et al. (2016) Vessel wall imaging for intracranial vascular disease evaluation. J Neurointerv Surg 8:1154-1159